Lesson 6: Principles of Data Science by Mohammad Hajiaghayi: Data Collection and Loading Tools
In this session, we discussed data collection and loading tools and techniques. More precisely in this class, we covered a range of topics essential to data science, including motivation, fundamental theories, and practical tools like Amazon AutoGluon https://docs.aws.amazon.com/sagemaker...
for model optimization. Understanding these concepts is crucial in today's data-driven world.
We also delved into the significance of sourcing data, whether through web scraping, APIs, or other means. Startups often rely on such approaches to data acquisition to fuel their operations, leveraging information from various sources such as energy markets or public datasets.
Additionally, we explored different methods of obtaining data, such as direct downloads, simulations, or querying databases. Understanding the diverse avenues for data collection is fundamental to any data science endeavor. We also touched upon the transition from imperative coding to distributed systems, emphasizing the importance of assembling and debugging complex data pipelines.
#WebScraping, #APIs, #EnergyMarkets, #PublicDatasets, #DataMonetization, #DataSources, #DataHandling, #DataManipulation, #DataScience, #AutoGluon, #ProbabilityTheory, #GraphAlgorithms, #MachineLearning, #ModelOptimization, #IndustryStandards, #Tools, #Statistics,
#datacollection, #Simulation, #Databases, #Debugging, #ImperativeCoding, #DistributedSystems, #DataPipelines, #DataRepresentation, #CSV, #DataManipulation.
